In-Memory Computing with Memristor Content Addressable Memories for Pattern Matching.
content addressable memory
finite state machines
in-memory computing
memristors
Journal
Advanced materials (Deerfield Beach, Fla.)
ISSN: 1521-4095
Titre abrégé: Adv Mater
Pays: Germany
ID NLM: 9885358
Informations de publication
Date de publication:
Sep 2020
Sep 2020
Historique:
received:
19
05
2020
revised:
24
06
2020
pubmed:
8
8
2020
medline:
2
7
2021
entrez:
8
8
2020
Statut:
ppublish
Résumé
The dramatic rise of data-intensive workloads has revived application-specific computational hardware for continuing speed and power improvements, frequently achieved by limiting data movement and implementing "in-memory computation". However, conventional complementary metal oxide semiconductor (CMOS) circuit designs can still suffer low power efficiency, motivating designs leveraging nonvolatile resistive random access memory (ReRAM), and with many studies focusing on crossbar circuit architectures. Another circuit primitive-content addressable memory (CAM)-shows great promise for mapping a diverse range of computational models for in-memory computation, with recent ReRAM-CAM designs proposed but few experimentally demonstrated. Here, programming and control of memristors across an 86 × 12 memristor ternary CAM (TCAM) array integrated with CMOS are demonstrated, and parameter tradeoffs for optimizing speed and search margin are evaluated. In addition to smaller area, this memristor TCAM results in significantly lower power due to very low programmable conductance states, motivating CAM use in a wider range of computational applications than conventional TCAMs are confined to today. Finally, the first experimental demonstration of two computational models in memristor TCAM arrays is reported: regular expression matching in a finite state machine for network security intrusion detection and definable inexact pattern matching in a Levenshtein automata for genomic sequencing.
Identifiants
pubmed: 32761709
doi: 10.1002/adma.202003437
doi:
Substances chimiques
Metals
0
Oxides
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e2003437Subventions
Organisme : Office of the Director of National Intelligence
Organisme : Intelligence Advanced Research Projects Activity
ID : 2017-17013000002
Organisme : Army Research Office
ID : W911NF-19-1-0494
Informations de copyright
© 2020 Wiley-VCH GmbH.
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